\reslheading{论文及落地场景}
\begin{figure}[h]
  \centering
  \includegraphics[width=0.8\textwidth]{fig/Aird-Timeline-中文.jpg}
  \caption{Aird技术发展时间线}
\end{figure}
  
  \begin{itemize}[leftmargin=*]
    \item \textbf{Miaoshan Lu}, Shaowei An, Ruimin Wang, Jinyin Wang, Changbin Yu*. Aird: a computation-oriented mass spectrometry data format enables a higher compression ratio and less decoding time[J]. BMC Bioinformatics, 2022, 23(1): 35.
    \\\textbf{研究成果用于解决质谱数据文件过大、读取速率慢而导致的分析时间过长问题，最终将原需1小时的分析过程缩短至6分钟，文件大小减少90\%，后续所有质谱数据分析应用均基于本论文成果完成。}
    \item \textbf{Miaoshan Lu}, Hengxuan Jiang, Ruimin Wang, Shaowei An, Jiawei Wang, Changbin Yu*. Injectiondesign: web service of plate design with optimized stratified block randomization for modern GC/LC-MS-based sample preparation[J]. BMC Bioinformatics, 2023(24): 489.
    \\\textbf{研究成果用于实现质谱进样前处理过程中的关键质控算法以及规范化流程，落地工业软件Injection Pro，并完成产学研转换50余万元。}
    \item \textbf{Miaoshan Lu}, Junjie Tong, Weidong Fang, Jinyin Wang, Shaowei An, Ruimin Wang, Hengxuan Jiang, Changbin Yu*. Column storage enables edge computation of biological big data on 5G networks[J]. Mathematical Biosciences and Engineering, 2023, 20(9): 17197–17219.
    \\\textbf{研究成果用于提升质谱分析算法中的关键原子步骤-色谱峰提取的速率，将2秒左右的提取时间减少至10毫秒，为质谱大数据搜索引擎提供可行性。}
    \item Junjie Tong\textsuperscript{\#}, \textbf{Miaoshan Lu}\textsuperscript{\#}, Ruimin Wang, Shaowei An, Jinyin Wang, Tong Wang, Cong Xie, Changbin Yu*. How Much Storage Precision Can Be Lost: Guidance for Near-Lossless Compression of Untargeted Metabolomics Mass Spectrometry Data[J]. Journal of Proteome Research, 2024(1535–3893).
    \\\textbf{研究成果详细论证了质谱数据分析对精度的容忍度，为Aird微损压缩算法提供了理论和实验依据。}
    \item Ruimin Wang, \textbf{Miaoshan Lu}, Shaowei An, Jinyin Wang, Changbin Yu*. 3D-MSNet: a point cloud-based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data[J]. Bioinformatics, 2023, 39(5).
    \\\textbf{研究成果用于解决质谱分析算法中的关键原子步骤-色谱峰提取的准确性，通过3D点云技术完成无损色谱峰提取，该技术落地应用3D-MSNet。}
    \item Ruimin Wang, \textbf{Miaoshan Lu}, Shaowei An, Jinyin Wang, Changbin Yu*. G-Aligner: a graph-based feature alignment method for untargeted LC-MS-based metabolomics[J]. BMC Bioinformatics, 2023, 24(1): 431.
    \\\textbf{研究成果用于解决质谱分析算法中的色谱峰对齐算法，为质谱大数据标准化对齐提供关键算法，算法已应用于质谱多组学大数据平台MS-Galaxy中。}
    \item Jinyin Wang, \textbf{Miaoshan Lu}, Ruimin Wang, Shaowei An, Cong Xie, Changbin Yu*. StackZDPD: a novel encoding scheme for mass spectrometry data optimized for speed and compression ratio[J]. Scientific Reports, 2022, 12(1): 5384.
    \\\textbf{研究成果用于解决归档质谱数据的压缩能力，相较于面向计算场景的压缩算法，本算法进一步提升25\%的质谱数据压缩能力。}
    \item Shaowei An, \textbf{Miaoshan Lu}, Ruimin Wang, Jinyin Wang, Hengxuan Jiang, Cong Xie, Junjie Tong, Changbin Yu*. Ion entropy and accurate entropy-based FDR estimation in metabolomics[J]. Briefings in Bioinformatics, 2024, 25(2): bbae056.
    \\\textbf{研究提出了一种新的代谢组学峰鉴定策略，通过计算离子熵并且引入FDR评估策略，有效降低了色谱峰鉴定的假阳性比例。}
    \item Shaowei An, Ruimin Wang, \textbf{Miaoshan Lu}, Chao Zhang, Huafen Liu, Jinyin Wang, Changbin Yu*. MetaPro: a web-based metabolomics application for LC-MS data batch inspection and library curation[J]. Metabolomics, 2023, 19(57).
    \\\textbf{研究成果用于指导和实现代谢组学半靶向数据分析的全链路算法，落地工业软件MetaPro，并完成产学研转换250余万元。}
    \item Ruimin Wang, Hengxuan Jiang, \textbf{Miaoshan Lu}, Junjie Tong, Shaowei An, Jinyin Wang, Changbin Yu*. MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry[J]. BMC Bioinformatics, 2024, 25(1): 60.
    \\\textbf{研究成果用于指导和实现代谢组学靶向数据分析的全链路算法，落地工业软件MRMPro,并完成产学研转换20余万元。}
    \item Robin Schmid, Steffen Heuckeroth,Ansgar Korf,Aleksandr Smirnov,Owen Myers,Thomas S. Dyrlund,Roman Bushuiev,Kevin J. Murray,Nils Hoffmann,\textbf{Miaoshan Lu},et al. Integrative analysis of multimodal mass spectrometry data in MZmine 3[J]. Nature Biotechnology,  2023, 41(4): 447–449.
    \\\textbf{研究成果用于指导和实现代谢组学非靶向数据分析的全链路算法，并扩展了Aird格式在国际的影响力，进一步展示了Aird格式的优越性。}
    \item Jingying Chen, Yaohan Li, Jingjing Chen, Ruimin Wang, \textbf{Miaoshan Lu}, Changbin Yu*. Miniature mass spectrometer–based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine[J]. Analytical and Bioanalytical Chemistry, 2024(1618–2650).
    \\\textbf{研究成果用于验证小型质谱仪在实时监测中的稳定性与灵敏度，为“高通量质谱做发现-小质谱做快速检测”提供了实验基础与可行性论证。}
 \end{itemize}